针对以下代码遇到此错误：

stage_string = [StringIndexer(inputCol=c, outputCol=c + "_string_encoded")  for c in categorical_columns]stage_one_hot = [OneHotEncoder(inputCol=c + "_string_encoded", outputCol=c + "_one_hot") for c in categorical_columns]assembler = VectorAssembler(inputCols=feature_list, outputCol="features")rf = RandomForestClassifier(labelCol="output", featuresCol="features")pipeline = Pipeline(stages=[stage_string,stage_one_hot,assembler, rf]) pipeline.fit(df)

Cannot recognize a pipeline stage of type <class 'list'>.Traceback (most recent call last):  File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/ml/base.py", line 132, in fit    return self._fit(dataset)  File "/usr/lib/spark/python/lib/pyspark.zip/pyspark/ml/pipeline.py", line 97, in _fit    "Cannot recognize a pipeline stage of type %s." % type(stage))TypeError: Cannot recognize a pipeline stage of type <class 'list'>.

回答：

问题出在这一语句上pipeline = Pipeline(stages=[stage_string,stage_one_hot,assembler, rf])，其中stage_string和stage_one_hot是PipelineStage的列表，而assembler和rf是单个的管道阶段。

请按以下方式修改您的语句：

stages = stage_string + stage_one_hot + [assembler, rf]pipeline = Pipeline(stages=stages)